Hand raised in anticipation, you eagerly awaited your kid to score the winning goal as your smartphone recorded that shining moment. Unfortunately, the footage that you captured was this grainy, shaky, and unwatchable nightmare.
Yep, you were the boomer parent who still uses those archaic phones without proper stabilization features and crappy camera modules.
Five years ago, you would have contemplated deleting such an embarrassing shot. Today, you just shrug it off. Because you know for certain that AI can recreate that moment perfectly just for you.
Phase 01: The Transformation
And no, we are not even talking about the far or near future. Tools today like Topaz Video AI, Runway Gen-2, Pika, and Magnific are already transforming wedding footage into cinematic masterpieces, turning old skateboarding clips into fantastic 4K showcases, and breathing new life into home movies that might even be older than you.
Sharpening details is just a start. These tools also hallucinate motion, light, detail, and context from minimal input. As Runway CEO Cristóbal Valenzuela explains, “What’s possible today with these models was unthinkable in the wildest dreams of anyone even a year or two ago.”
Basically, these algorithms predict frames based on data training rather than reconstructing exact pixels. They might fill in face details, finger motion, clothing folds, or even scrolling backgrounds based on what should be there, filling the void of what was originally captured.
Meta’s EmuVideo, for example, demonstrates that restoration, not generation (from scratch) is the key, a combined effort between text-to-image creation and frame-to-video development. Magnific AI’s approach also exemplifies consumer-level hallucination, represented by the “creativity” level adjustment (an ironic word to use with generate AI, sure), which directly translates to how much the tool might hallucinate new details into images. As one authoritative website about the topic notes: “Magnific AI takes a different approach to Generative AI upscaling by allowing you to dive deep into an image and create amazing unseen details at high magnification.”
Most of these tools now work on smartphones and other smaller, more mobile devices via cloud processing, allowing professional-grade enhancement to be available at any level and practically anywhere. And yes, with just these tools right now in 2025, one can easily imagine early YouTube videos are being resurrected, family VHS tapes transformed, and even grainy concert clips reborn as crystal-clear memories.
Phase 02: The Cultural Paradox
So, now that you know these tools exist and what they can generally do, let’s ask the next natural question: which is better? Surprisingly, given the choice between original footage and AI-enhanced versions, a good number of random people consistently choose the artificial upgrade. Quite in contrast to some of the other artistic avenues of generative AI, where there is a strong sentiment against the use of so-called “AI slop.”
Beyond Personal Moments
First argument supporting the case: memory enhancement. In other words, making those “once in a lifetime” moments even bigger than life. Wedding videographers, for instance, now sell “AI-enhanced packages” as premium services. At least one wedding videography service, at least, reports great client satisfaction even with just simple (but targeted and strategic) AI upscaling, ending one of the comprehensive reports with “our client was in awe over the final result.”
Of course, shorter moments, especially the ones with high potential virality, are also subject to the enhancements of AI editing. In this particular case, TikTok’s AI Alive feature showcases the transformation of static photos into cinematic clips. For example, turning a sunset photo into dynamic footage where “the sky gradually shifts hues, clouds drift lazily, and ambient sounds of waves crashing in the distance bring the scene to life.”
Institutional Adoption
Second, and probably the most powerful argument that supports AI enhancement: archival preservation. Probably the most fascinating of these at the moment is the enhancement of very old-timey footage. Think of pre-World War I, or even the 19th century era! YouTubers are systematically enhancing historical footage using AI tools, transforming grainy 1896 clips into full-color, pristine 4K video at 60 frames per second.
That being said, this enthusiasm also had its fair share of controversy. In the same TechSpot article, Luke McKernan, lead curator at the British Library, argues these techniques “turn out subjective interpretations of the original content” that remove “authenticity and accuracy of the source footage.” While most are mesmerized by the “what if” scenarios these “time travel” videos provide, the more classical folks will still debate whether AI enhancement preserves or corrupts historical documentation.
Phase 03: From Archives to Instagram
Moving from independent and small-business use to bigger, more corporate applications, Hollywood archives are also hard at work at systematic historical footage enhancement. Institutions like museums are using AI to clean up exhibition materials, and news organizations are quietly improving the visual quality of archival clips.
But again, these are simply tools, and their purpose is custom-built to the scale and direct benefit of its user. The result is a single continuous path from institutional archives to social media feeds. The line between professional restoration and casual enhancement has effectively disappeared. A museum’s AI-restored historical footage and an influencer’s enhanced vacation video now use remarkably similar technological approaches.
If you don’t know whose is who and which is which, then attribution for supposedly “genuine” archival footage becomes tricky. And yes, the ol’ reliable techniques of cropping and screenshotting to circumvent labels still apply here.
And while the video wars rage on today, trust me, you haven’t seen the real battle yet.
Phase 04: The Restoration Controversy
The very democratization that equalized the playing field for both casual and professionals in the world of AI has sparked a fundamental question: at what point does enhancement become fabrication? Even without discussing the myriad of controversies about AI-generated data over the last few years, the fundamental issue is that both “restoration” and “generation” are at best, just sophisticated guesswork.
Yes, YouTubers use AI to enhance century-old films, adding colors that never existed and smoothing motion with interpolated frames. Historians argue that these are still creative interpretations, an approximation of what might be true, but are still not the absolute truth. Can you imagine if the well-crafted old-timey “footage” of the Titanic spreading around online begins to be the definitive record in public memory? It may be emotionally compelling, but it is still historically blown out of proportion.
Indeed, the line between preservation and propaganda becomes dangerously thin when AI enhancement creates false memories of historical events. Much more so when they become more and more convincing each passing year.
The (Disturbing) Memory Future of Restoration
The restoration of old media and the fixing of bad videos will eventually lead to current AI memory systems tracking preferences and histories accurately. In fact, just regular text-based generative AI is already doing that, and is not only about AI sexting prompts. As platforms integrate sophisticated video generation, some which already did, the line between remembered experience and AI-enhanced reconstruction would probably disturbingly disappear.
Your AI companion might show your childhood home “enhanced” with algorithmic details. Implications extend beyond personal memory. If platforms miss labeling AI content, personal archives become indistinguishable from creative fiction; family memories get algorithmically improved beyond recognition. The worst part is that everything makes too much perfect sense, that our brains won’t even fight against it. We would most likely embrace this sophisticated, yet fabricated memory all too quickly.
The technology preserving our past also has the equal chance of rewriting it, innocently or maliciously. MIT research suggests widespread AI labeling could increase public skepticism of all media, questioning authentic content; the cure may poison trust in genuine documentation.
… and no, your kid never actually came near to scoring that goal after all.
